OPTIMIZATION OF SURFACE ROUGHNESS IN AISI D-3 MACHINING USING POWDER-MIXED ELECTRICAL DISCHARGE MACHINING WITH ALUMINUM POWDER

This study investigates the impact of powder-mixed electrical discharge machining (PMEDM) with aluminum powder on surface roughness (SR), benchmarking its performance against traditional electrical discharge machining (EDM). This research demonstrates a significant enhancement in SR through the incorporation of aluminum powder into the dielectric fluid. A detailed analysis was conducted to evaluate the effects of critical process parameters — current (I), voltage (GV), powder concentration (PC), pulse duration (CT), and duty factor (DF) — on SR. The findings reveal that I, GV, and PC have a pronounced influence on SR, while CT and DF exhibit minimal effects. Optimal machining conditions were established as [Formula: see text] [Formula: see text]A, [Formula: see text] [Formula: see text]V, [Formula: see text]s, [Formula: see text] [Formula: see text]g/L, and [Formula: see text], achieving an impressive SR of 2.78[Formula: see text] [Formula: see text]m. Additionally, this study analyzed the thickness of the metal recast layer, which ranged from 1[Formula: see text] [Formula: see text]m to 25[Formula: see text] [Formula: see text]m. Notably, mixtures of aluminum and silicon carbide powders resulted in thicker recast layers compared to single powder setups. This research highlights the potential of PMEDM to enhance machining outcomes and identifies existing limitations in the tested parameters. It suggests future studies exploring alternative dielectrics, powder materials, and workpiece combinations to further refine PMEDM performance and broaden its industrial applicability.

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Publication Details

Journal
Surface Review and Letters
Published
2025-02-21
DOI
https://doi.org/10.1142/s0218625x2540013x
Primary Topic
Advanced Machining and Optimization Techniques
Type
article
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article

OPTIMIZATION OF SURFACE ROUGHNESS IN AISI D-3 MACHINING USING POWDER-MIXED ELECTRICAL DISCHARGE MACHINING WITH ALUMINUM POWDER

Shailesh Shirguppikar, Ly Nguyen Trong, Vaibhav Ganachari, Toan Nguyen Duc et al.
Surface Review and Letters
Advanced Machining and Optimization Techniques
article

OPTIMIZATION OF SURFACE ROUGHNESS IN AISI D-3 MACHINING USING POWDER-MIXED ELECTRICAL DISCHARGE MACHINING WITH ALUMINUM POWDER

Shailesh Shirguppikar, Ly Nguyen Trong, Vaibhav Ganachari, Toan Nguyen Duc, Nguyen Huu Phan
article en

Abstract

This study investigates the impact of powder-mixed electrical discharge machining (PMEDM) with aluminum powder on surface roughness (SR), benchmarking its performance against traditional electrical discharge machining (EDM). This research demonstrates a significant enhancement in SR through the incorporation of aluminum powder into the dielectric fluid. A detailed analysis was conducted to evaluate the effects of critical process parameters — current (I), voltage (GV), powder concentration (PC), pulse duration (CT), and duty factor (DF) — on SR. The findings reveal that I, GV, and PC have a pronounced influence on SR, while CT and DF exhibit minimal effects. Optimal machining conditions were established as [Formula: see text] [Formula: see text]A, [Formula: see text] [Formula: see text]V, [Formula: see text]s, [Formula: see text] [Formula: see text]g/L, and [Formula: see text], achieving an impressive SR of 2.78[Formula: see text] [Formula: see text]m. Additionally, this study analyzed the thickness of the metal recast layer, which ranged from 1[Formula: see text] [Formula: see text]m to 25[Formula: see text] [Formula: see text]m. Notably, mixtures of aluminum and silicon carbide powders resulted in thicker recast layers compared to single powder setups. This research highlights the potential of PMEDM to enhance machining outcomes and identifies existing limitations in the tested parameters. It suggests future studies exploring alternative dielectrics, powder materials, and workpiece combinations to further refine PMEDM performance and broaden its industrial applicability.

Surface Review and LettersVol. 32(08)
Shivaji University (IN), Hanoi University of Industry (VN), Hanoi University of Science and Technology (VN)
Openalex Percentile: Top 98%
Advanced Machining and Optimization Techniques
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